YES! SOLVED! Once you have decomposed it from *.tar, do it again on the generated file, then you will see different josn files.

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@tiechengsu i am having the same problem, were you able to solve the issue?

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@bngksgl No, I used the previous dataset instead, which you can find here
https://app.dominodatalab.com/mtldata/yackathon/browse/yelp_dataset_challenge_academic_dataset
It's easier to import. The latest data combine several categories together, no idea have to import it.

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It's a .tar file, just decompress it again

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The latest data combine several categories together, no idea have to import it.

Does that mean reviews.josn and business.json,etc. are mixed stored int he file?

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Not really sure where you ppl r facing errors. I have edited the code to accept .json files explicitly and convert them to .csv. I have mentioned the filepath in main method explicitly instead of using arg.parse as in original code. Let me know if this helps.

Reference:

https://github.com/Yelp/dataset-examples/blob/master/json_to_csv_converter.py

"""Convert the Yelp Dataset Challenge dataset from json format to csv.
import argparse
import collections
import csv
import json
def read_and_write_file(json_file_path, csv_file_path, column_names):
"""Read in the json dataset file and write it out to a csv file, given the column names."""
with open(csv_file_path, 'w') as fout:
csv_file = csv.writer(fout)
csv_file.writerow(list(column_names))
with open(json_file_path, encoding = 'utf8') as fin:
for line in fin:
line_contents = json.loads(line)
csv_file.writerow(get_row(line_contents, column_names))
def get_superset_of_column_names_from_file(json_file_path):
"""Read in the json dataset file and return the superset of column names."""
column_names = set()
with open(json_file_path, encoding = 'utf8') as fin:
for line in fin:
line_contents = json.loads(line)
column_names.update(
set(get_column_names(line_contents).keys())
)
return column_names
def get_column_names(line_contents, parent_key=''):
"""Return a list of flattened key names given a dict.
Example:
line_contents = {
'a': {
'b': 2,
'c': 3,
},
}
will return: ['a.b', 'a.c']
These will be the column names for the eventual csv file.
"""
column_names = []
for k, v in line_contents.items():
column_name = "{0}.{1}".format(parent_key, k) if parent_key else k
if isinstance(v, collections.MutableMapping):
column_names.extend(
get_column_names(v, column_name).items()
)
else:
column_names.append((column_name, v))
return dict(column_names)
def get_nested_value(d, key):
"""Return a dictionary item given a dictionary d and a flattened key from get_column_names.

Example:
    d = {
        'a': {
            'b': 2,
            'c': 3,
            },
    }
    key = 'a.b'
    will return: 2

"""
if '.' not in key:
    if key not in d:
        return None
    return d[key]
base_key, sub_key = key.split('.', 1)
if base_key not in d:
    return None
sub_dict = d[base_key]
return get_nested_value(sub_dict, sub_key)

def get_row(line_contents, column_names):
"""Return a csv compatible row given column names and a dict."""
row = []
for column_name in column_names:
line_value = get_nested_value(
line_contents,
column_name,
)
if isinstance(line_value, str):
row.append('{0}'.format(line_value.encode('utf-8')))
elif line_value is not None:
row.append('{0}'.format(line_value))
else:
row.append('')
return row
if(name == 'main'):
"""Convert a yelp dataset file from json to csv."""
json_file = []
json_file.append('D:\YELP Dataset\yelp_academic_dataset_business.json'); #args.json_file
json_file.append('D:\YELP Dataset\yelp_academic_dataset_checkin.json');
json_file.append('D:\YELP Dataset\yelp_academic_dataset_review.json');
json_file.append('D:\YELP Dataset\yelp_academic_dataset_tip.json');
json_file.append('D:\YELP Dataset\yelp_academic_dataset_user.json');
csv_file = []
for i in range(5):
csv_file.append('{}.csv'.format((json_file[i])[0:len(json_file[i])-5]))
column_names = get_superset_of_column_names_from_file(json_file[i])
read_and_write_file(json_file[i], csv_file[i], column_names)
print('{} converted to {} successfully.'.format(json_file[i], csv_file[i]))

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@CAVIND46016 are you able to post your code in a formatted snippet? Using it in my compiler is producing indentation errors. Thank you!

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@dotdose : Have a look at the code here, this should work better.
https://github.com/CAVIND46016/Yelp-Reviews-Dataset-Analysis/blob/master/json_to_csv_converter.py

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